1. Field of the Invention
The present invention relates to techniques for performing oilfield operations relating to subterranean formations having reservoirs therein. More particularly, the invention relates to techniques for performing oilfield operations involving an analysis of reservoir operations, and their impact on such oilfield operations.
2. Background of the Related Art
Oilfield operations, such as surveying, drilling, wireline testing, completions, simulation, planning and oilfield analysis, are typically performed to locate and gather valuable downhole fluids. Various aspects of the oilfield and its related operations are shown in FIGS. 1A-1D. As shown in FIG. 1A, surveys are often performed using acquisition methodologies, such as seismic scanners to generate maps of underground structures. These structures are often analyzed to determine the presence of subterranean assets, such as valuable fluids or minerals. This information is used to assess the underground structures and locate the formations containing the desired subterranean assets. Data collected from the acquisition methodologies may be evaluated and analyzed to determine whether such valuable items are present, and if they are reasonably accessible.
As shown in FIG. 1B-1D, one or more wellsites may be positioned along the underground structures to gather valuable fluids from the subterranean reservoirs. The wellsites are provided with tools capable of locating and removing hydrocarbons from the subterranean reservoirs. As shown in FIG. 1B, drilling tools are typically advanced from the oil rigs and into the earth along a given path to locate the valuable downhole fluids. During the drilling operation, the drilling tool may perform downhole measurements to investigate downhole conditions. In some cases, as shown in FIG. 1C, the drilling tool is removed and a wireline tool is deployed into the wellbore to perform additional downhole testing.
After the drilling operation is complete, the well may then be prepared for simulation. As shown in FIG. 1D, wellbore completions equipment is deployed into the wellbore to complete the well in preparation for the simulation of fluid therethrough. Fluid is then drawn from downhole reservoirs, into the wellbore and flows to the surface. Simulation facilities are positioned at surface locations to collect the hydrocarbons from the wellsite(s). Fluid drawn from the subterranean reservoir(s) passes to the simulation facilities via transport mechanisms, such as tubing. Various equipments may be positioned about the oilfield to monitor oilfield parameters and/or to manipulate the oilfield operations.
During the oilfield operations, data is typically collected for analysis and/or monitoring of the oilfield operations. Such data may include, for example, subterranean formation, equipment, historical and/or other data. Data concerning the subterranean formation is collected using a variety of sources. Such formation data may be static or dynamic. Static data relates to, for example, formation structure and geological stratigraphy that define the geological structure of the subterranean formation. Dynamic data relates to, for example, fluids flowing through the geologic structures of the subterranean formation over time. Such static and/or dynamic data may be collected to learn more about the formations and the valuable assets contained therein.
Sources used to collect static data may be seismic tools, such as a seismic truck that sends compression waves into the earth as shown in FIG. 1A. These waves are measured to characterize changes in the density of the geological structure at different depths. This information may be used to generate basic structural maps of the subterranean formation. Other static measurements may be gathered using core sampling and well logging techniques. Core samples may be used to take physical specimens of the formation at various depths as shown in FIG. 1B. Well logging typically involves deployment of a downhole tool into the wellbore to collect various downhole measurements, such as density, resistivity, etc., at various depths. Such well logging may be performed using, for example, the drilling tool of FIG. 1B and/or the wireline tool of FIG. 1C. Once the well is formed and completed, fluid flows to the surface using simulation tubing as shown in FIG. 1D. As fluid passes to the surface, various dynamic measurements, such as fluid flow rates, pressure, and composition may be monitored. These parameters may be used to determine various characteristics of the subterranean formation.
Sensors may be positioned about the oilfield to collect data relating to various oilfield operations. For example, sensors in the drilling equipment may monitor drilling conditions, sensors in the wellbore may monitor fluid composition, sensors located along the flow path may monitor flow rates, and sensors at the processing facility may monitor fluids collected. Other sensors may be provided to monitor downhole, surface, equipment or other conditions. The monitored data is often used to make decisions at various locations of the oilfield at various times. Data collected by these sensors may be further analyzed and processed. Data may be collected and used for current or future operations. When used for future operations at the same or other locations, such data may sometimes be referred to as historical data.
The processed data may be used to predict downhole conditions, and make decisions concerning oilfield operations. Such decisions may involve well planning, well targeting, well completions, operating levels, simulation rates and other operations and/or conditions. Often this information is used to determine when to drill new wells, re-complete existing wells, or alter wellbore simulation.
Data from one or more wellbores may be analyzed to plan or predict various outcomes at a given wellbore. In some cases, the data from neighboring wellbores or wellbores with similar conditions or equipment may be used to predict how a well will perform. There are usually a large number of variables and large quantities of data to consider in analyzing oilfield operations. It is, therefore, often useful to model the behavior of the oilfield operation to determine the desired course of action. During the ongoing operations, the operating conditions may need adjustment as conditions change and new information is received.
Techniques have been developed to model the behavior of various aspects of the oilfield operations, such as geological structures, downhole reservoirs, wellbores, surface facilities as well as other portions of the oilfield operation. Examples of these modeling techniques are shown in Patent/Publication/Application Nos. U.S. Pat. No. 5,992,519, WO2004/049216, WO1999/064896, WO2005/122001, U.S. Pat. No. 6,313,837, US2003/0216897, US2003/0132934, US2005/0149307, US2006/0197759, U.S. Pat. No. 6,980,940, US2004/0220846, and Ser. No. 10/586,283. Techniques have also been developed for performing reservoir simulation operations. See, for example, Patent/Publication/Application Nos. U.S. Pat. No. 6,230,101, U.S. Pat. No. 6,018,497, U.S. Pat. No. 6,078,869, GB2336008, U.S. Pat. No. 6,106,561, US2006/0184329, U.S. Pat. No. 7,164,990.
Examples of oilfield operations include Enhanced Oil Recovery (EOR) processes to extend field life and increase ultimate oil recovery from naturally depleting reservoirs. Enhanced oil recovery can begin at any time during the productive life of an oil reservoir. Its purpose is not only to restore formation pressure, but also to improve oil displacement or fluid flow in the reservoir. The three major types of enhanced oil recovery operations are chemical flooding (alkaline flooding or micellar-polymer flooding), miscible displacement (carbon dioxide injection or hydrocarbon injection), and thermal recovery (steamflood, waterflood, or in-situ combustion). The optimal application of each type depends on reservoir temperature, pressure, depth, net pay, permeability, residual oil and water saturations, porosity and fluid properties such as oil API gravity and viscosity.
Steamflood is a method of thermal recovery in which steam generated at surface is injected into the reservoir through specially distributed injection wells. When steam enters the reservoir, it heats up the crude oil and reduces its viscosity. The heat also distills light components of the crude oil, which condense in the oil bank ahead of the steam front, further reducing the oil viscosity. The hot water that condenses from the steam and the steam itself generate an artificial drive that sweeps oil toward producing wells. Another contributing factor that enhances oil production during steam injection is related to near-wellbore cleanup. In this case, steam reduces the interfacial tension that ties paraffins and asphaltenes to the rock surfaces while steam distillation of crude oil light ends creates a small solvent bank that can miscibly remove trapped oil.
Waterflooding is among the oldest and perhaps most economical of EOR processes. Hot waterflooding is a method of thermal recovery in which hot water is injected into a reservoir through specially distributed injection wells. Hot waterflooding reduces the viscosity of the crude oil, allowing it to move more easily toward production wells. Hot waterflooding, also known as hot water injection, is typically less effective than a steam-injection process because water has lower heat content than steam. Nevertheless, it is preferable under certain conditions such as formation sensitivity to fresh water.
Current high oil prices provide incentive for companies to look deeper into their reservoir portfolios for additional EOR (e.g., waterflooding) opportunities. Time and information constraints can limit the depth and rigor of such a screening evaluation. Time is reflected by the effort of screening a vast number of reservoirs for the applicability of implementing an EOR (e.g., waterflooding), whereas information is reflected by the availability of data (consistency of measured and modeled data) with which to extract significant knowledge necessary to make good development decisions.
Examples of oilfield operations also include the installation of intelligent completions to improve the economics of production. These wells allow access not only to marginal reservoirs, for which dedicated production might not be economic, but also accelerate the recovery. Monitoring flow-control and other devices can be used to manage the production from the commingled reservoirs and optimize the recovery.
Regulatory bodies usually demand that the operator can allocate the production to the individual reservoirs for reserves accounting purposes. Unless flow meters for each completion are installed, back-allocation from the wellhead to the completion is difficult to achieve. Traditional methods that could deliver the production share in real-time fail to provide accurate results when the inflow performance of one completion changes. Numerical modeling, which accounts for the mobility change and the resulting re-distribution of the pressure in the open system of the completion, is time consuming and cannot be used for back-allocation in real-time.
Despite the development and advancement of reservoir simulation techniques in oilfield operations, there remains a need to consider the effects of large number of reservoirs and uncertainty in accurate numerical well models on oilfield operations. It would be desirable to provide techniques to screen large number of candidates for selecting, planning and/or implementing oilfield operations based on static and dynamic aspects of the oilfield. It would also be desirable to perform back-allocation of commingling wells in real-time. It is further desirable that such techniques selectively consider desired parameters, such as measured data or modeled data with uncertainty in accuracy or consistency. Such desired techniques may be capable of one of more of the following, among others: providing screening capability for reducing the number of reservoir candidates (i.e., reservoir candidates to be evaluated in mode detail for selection to perform oilfield operations) by one or more order of magnitude, providing modeling capability to evaluate sensitivities and uncertainties of influencing parameters, and providing modeling capability to speed up the screening process without jeopardizing the quality of the results.